New ways of making physical products that are faster, cheaper, and more precise. From 3D printing to laser welding, advanced fabrication changes how things are built.

A computer’s architecture — how its hardware is organised — shapes what it’s good at. Alternatives like neuromorphic and analog chips are suited to the kinds of information processing that raise the ceiling for physical intelligence - sensing and reacting quickly on very little energy, learning continuously in the wild, and processing billions of messy inputs at once.

Engineered systems capable of holding up in a changing world with infinite possibilities — artificial intelligence built to listen, adapt, and discover something new and meaningful, across domains.

Building products one atom at a time. This could unlock entirely new materials and technologies that aren’t possible with today’s manufacturing - a new level of precision and performance.

Power grids that can monitor themselves, make decisions, and adapt automatically in real time. This could make energy cheaper, more reliable, and more resilient.

Factories, mines, fabs, and other industrial sites that can largely operate themselves. These make critical industries safer, cheaper, and more productive, allowing us to reach the scale required to impact the physical world.

Using AI and robots to design experiments, run them automatically, and discover new ideas faster than people alone could.

Using electricity to help living cells (biology) make the fuels, chemicals, and materials we rely on every day.

Combining living tissues with machines to unlock capabilities traditional technology can’t match. Think biological computers, more efficient sensors, and entirely new kinds of machines.

Biological compute substrates are things that are alive (or built from living parts) used as hardware for intelligent machines. They inherit the computing tricks life already figured out: sensing and reacting with almost no energy, learning and adapting without reprogramming, repairing or replicating themselves, changing physically as conditions shift, and coping with ambiguity instead of needing perfect inputs.

Tiny, efficient power sources built directly into devices and machines (like robots). These reduce the need for cables, batteries, or connection to the grid.

AI built into physical machines and robots that learn by doing, improving their models by interacting with the world. The same hardware that senses and moves also runs the learning, instead of relying on a distant cloud or central brain.

Giving robots and other systems the ability to understand and interact with the physical world.

The same process that powers the sun. If we can recreate it on Earth, we could provide abundant clean energy using only tiny amounts of fuel.

Using AI to engineer biology as a giant design space. Machine learning mines billions of years of evolution for clever solutions and to learn the rules of what’s possible, and synthetic biology builds new molecules, medicines, and machines using life’s own toolkit.

Materials that can grow, repair themselves, or respond to their surroundings. Making everything from buildings to robots stronger, smarter, and longer lasting.

Most energy is wasted as heat before it reaches where we need it. Lossless energy systems aim to deliver more of that energy exactly where it should go.

Materials engineered to have properties that don’t exist in nature. They can bend light, sound, or heat in remarkable ways, unlocking entirely new technologies.

Instead of relying on chemistry to organise itself, molecular control systems precisely direct how molecules behave. This could transform medicine, manufacturing, and materials science.

Tiny machines built from individual molecules. They can perform tasks inside our bodies or manufacture materials with unbeatable precision.

Machines that learn and think through many senses at once, like animals do. They weave sight, sound, touch, and other beyond-human signals into one rich picture of the world instead of relying on a single feed or text labels.

Reimagining how goods move around the world. From autonomous airships to new shipping networks, better logistics could make global trade faster, cheaper, and more resilient.

Superintelligence is intelligence that far exceeds human capability and comprehension. Planetary superintelligence comes from reading, understanding, and learning from the world’s complex natural systems — swarms of ants coordinating, plants communicating, the planet regulating itself. The result is a shared web of explanations and solutions to problems no one mind—living or machine—could produce alone.

Evolution has spent millions of years solving movement through Earth’s wildest places. Robofauna borrows nature’s best designs to build more capable robots, from climbing like geckos to flying like birds.

Machines and materials that can build or repair themselves. This could unlock massive scale robotics with capabilities that biology already has.

Robots made from novel and flexible materials instead of just rigid metal. They can move more safely around our world and handle delicate objects with care.

Historically, power stations have relied on spinning machines (turbines). Solid-state generation produces electricity directly, making systems much simpler and therefore more reliable and easier to maintain.

Superconductors move electricity with almost no energy loss and respond in milliseconds. They make future power grids faster, more stable, and more reliable, allowing us to build AI data centres and EV charging stations without breaking the grid.

Transmutation allows us to change one type of atom into another. It could be used to create scarce materials, improve cancer treatments, and reduce nuclear waste.

Building every step of the manufacturing process under one roof, from raw materials to finished products. This can improve quality, reduce costs, and speed up innovation loops.

Living things, computer programs, and robots all need a basic sense of what things are and how they behave to survive and act in their world. A world model is that mental model—the compressed explanation of reality an intelligent system will learn and rely on while navigating new experiences, predicting what comes next, and acting in the world.